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Almost self-optimizing strategies for the adaptive control of diffusion processes

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Abstract

The ergodic control of a multidimensional diffusion process described by a stochastic differential equation that has some unknown parameters appearing in the drift is investigated. The invariant measure of the diffusion process is shown to be a continuous function of the unknown parameters. For the optimal ergodic cost for the known system, an almost optimal adaptive control is constructed for the unknown system.

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Author information

Authors and Affiliations

  1. Department of Mathematics, University of Kansas, Lawrence, Kansas

    T. E. Duncan (Professor) & B. Pasik-Duncan (Professor)

  2. Institute of Mathematics, Polish Academy of Sciences, Warsaw, Poland

    L. Stettner (Associate Professor)

Authors
  1. T. E. Duncan
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  2. B. Pasik-Duncan
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  3. L. Stettner
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Additional information

Communicated by R. Rishel

This research was partially supported by NSF Grants ECS-87-18026, ECS-91-02714, and ECS-91-13029.

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Duncan, T.E., Pasik-Duncan, B. & Stettner, L. Almost self-optimizing strategies for the adaptive control of diffusion processes. J Optim Theory Appl 81, 479–507 (1994). https://doi.org/10.1007/BF02193097

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